M. Teja Kiran Kumar
- Computer Vision and Pattern Recognition top 5%
- Human-Computer Interaction top 2%
- Biomedical Engineering
- Developmental and Educational Psychology top 10%
- Artificial Intelligence
- Co-authors
- D. Anil KumarE. Kiran KumarP. V. V. KishoreAnanth SastrySuman MalojiG. Anantha RaoDarshika G. PereraK. Praveen Kumar Rao
- Topics
- Human Pose and Action Recognition (16 papers)Hand Gesture Recognition Systems (11 papers)Gait Recognition and Analysis (11 papers)
- Cited by
- Human-Computer InteractionComputer Vision and Pattern RecognitionDevelopmental and Educational Psychology
- Partner nations
- IndiaUnited StatesNepal
In The Last Decade
M. Teja Kiran Kumar
17 papers receiving 344 citations
Peers
Comparison fields: 5 of 51
- Computer Vision and Pattern Recognition 226
- Human-Computer Interaction 212
- Biomedical Engineering 137
- Developmental and Educational Psychology 98
- Artificial Intelligence 50
Countries citing papers authored by M. Teja Kiran Kumar
This map shows the geographic impact of M. Teja Kiran Kumar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by M. Teja Kiran Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Teja Kiran Kumar more than expected).
Fields of papers citing papers by M. Teja Kiran Kumar
This network shows the impact of papers produced by M. Teja Kiran Kumar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by M. Teja Kiran Kumar. The network helps show where M. Teja Kiran Kumar may publish in the future.
Co-authorship network of co-authors of M. Teja Kiran Kumar
This figure shows the co-authorship network connecting the top 25 collaborators of M. Teja Kiran Kumar. A scholar is included among the top collaborators of M. Teja Kiran Kumar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with M. Teja Kiran Kumar. M. Teja Kiran Kumar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 19 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | Training Granular Convolution Neural Network with Depth Motion Maps along with Joint Angular Displacement Maps for Kinect based Human Action Recognition | 1 |
| 8 | 3 | |
| 9 | 34 | |
| 10 | 45 | |
| 11 | 42 | |
| 12 | 49 | |
| 13 | 17 | |
| 14 | 37 | |
| 15 | 62 | |
| 16 | 15 | |
| 17 | 21 | |
| 18 | 6 |
About M. Teja Kiran Kumar
M. Teja Kiran Kumar is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Biomedical Engineering, having authored 18 papers that have together received 362 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (16 papers), Hand Gesture Recognition Systems (11 papers) and Gait Recognition and Analysis (11 papers). The work is most often cited by research in Human-Computer Interaction (212 citations), Computer Vision and Pattern Recognition (226 citations) and Developmental and Educational Psychology (98 citations). M. Teja Kiran Kumar has collaborated with scholars based in India, United States and Nepal. Frequent co-authors include D. Anil Kumar, E. Kiran Kumar, P. V. V. Kishore, Ananth Sastry, Suman Maloji, G. Anantha Rao, Darshika G. Perera, K. Praveen Kumar Rao, B. T. P. Madhav and K. Murali. Their work appears in journals such as IEEE Access, Neurocomputing and IEEE Transactions on Multimedia.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.